This invention relates to physiological monitoring systems and methods, and more particularly to physiological monitoring systems and methods which provide improved measurements of physiological parameters.
A medical monitoring or diagnostic device generally includes the ability to perform a measurement to obtain an estimate of the true value of a physiological parameter. This estimate is then used by a clinician to derive information concerning a patient""s physical state, for the purpose of determining or monitoring a course of action with regard to the patient""s medical care. An implicit assumption in this process is that the estimate of the physiological parameter provided by the measurement is identical to the actual, true value.
In actuality, the estimate of a parameter provided by a measurement has an inherent error, or difference between the estimated (measured) value and the true value. A measurement system may be such that it produces a random error (with an average value of zero), or it may be biased, such that the average error of the estimates is not equal to zero.
Concepts well understood in medical science are that of the sensitivity and specificity of a test. A binary estimate is one that can have 1 of 2 values: positive or negative, yes or no, present or absent, etc. For example, in the case of a binary parameter whose value can be positive or negative, the probability that any one measurement or estimate yields a positive response or prediction when the true value actually is positive is the xe2x80x9csensitivityxe2x80x9d of the measurement. The sensitivity is thus the probability of detecting a true positive outcome. The probability that any one measurement or estimate yields a negative response or prediction when the true value actually is negative is the xe2x80x9cspecificityxe2x80x9d of the measurement. The specificity is thus the probability of detecting a true negative outcome.
An ideal estimate or predictor would be one whose sensitivity and specificity are both 100%; that is, one in which there is zero probability of false detection, either false positive or false negative. Physically realizable measurements, however, rarely achieve this ideal. They instead typically have both sensitivity and specificity less than 100%.
It is well known in the art that the sensitivity and specificity of a measurement system can be biased by design either toward higher sensitivity at the expense of lower specificity, or toward higher specificity at the expense of lower sensitivity. The possible operating points of a measurement system can be described by the Receiver Operating Characteristic (ROC) curve. A hypothetical ROC curve is shown in FIG. 1. Actual ROC curves may be of different forms, but all exhibit a trade-off of sensitivity for specificity.
A binary estimate of a binary parameter translates directly to a predicted value for the parameter. It is also well understood in the art that predicted values can be obtained from continuous estimators. A threshold value may be applied to a continuous estimator of a binary parameter in order to provide a binary prediction. For example, if the value of the estimate is less than the threshold, the parameter is predicted to have one of the binary states. If the value of the estimate is greater than or equal to the threshold, the parameter is predicted to have the other binary state. The relationship between the estimator and the parameter may be modeled from experimental data as a probability of response, as shown in FIG. 2. The value of the estimator at which the probability of response is 50% is used as the threshold value in the preferred embodiment.
In a similar manner, multiple thresholds may be applied to a continuous estimator to predict the value of an ordinal parameter. For example, the Modified Observer""s Assessment of Alertness/Sedation scale is commonly used to quantify an anesthetized surgical patient""s level of sedation. A set of five ordinal thresholds may be applied to a single continuous estimator of the patient""s sedation state to obtain a predicted sedation state.
The case of a continuous estimator used to predict an ordinal parameter may be extended to that of a continuous estimator used to predict the value of a continuous parameter. The relationship between the estimator and the parameter it predicts need not be linear, just as the threshold need not be evenly spaced in the case of an ordinal estimator. Any continuous parameter (e.g., a patient""s state of sedation) may be considered to be a set of discrete ordinal states, each of which may be estimated by applying an appropriate set of threshold values to the continuous predictor. While each state is distinct, they are all steps on a continuum of states from one end of the state range to the other. Thus the concept of a ROC curve may be applied to the overall continuum of states as well as any pair of states and the performance of the estimator may be tuned to vary its sensitivity and specificity with respect to the full range of the parameter. It is important to note that an explicit threshold need not be applied to a continuous estimator in order to use the ROC concept; the probability of response is implied through the correlation between the estimator and the underlying parameter.
If a physically realizable system does not have both 100% sensitivity and specificity, then an important design issue is the point on the ROC curve corresponding to the actual sensitivity and specificity of the measurement. This is the operating point. In the case of a continuous estimator, varying the threshold value shifts the operating point along the ROC curve. The optimal location for the operating point on the ROC curve is preferably derived by means of a cost-benefit analysis. Weighing the cost of a false detection (both false positive and false negative) against the benefit of a correct detection performs such an analysis. When the cost and benefit are not equivalent, it may be desirable to shift the operating point to bias the prediction toward increased sensitivity or specificity. For example, a system designed to screen patients for the presence of a fatal disease may be designed to have very high sensitivity at the expense of low specificity. The increased detection rate afforded by the elevated sensitivity may be well worth the extra testing required to rule out false positives. The design procedure, however, requires that a choice be made between high sensitivity and high specificity in order to specify an operating point.
U.S. Pat. No. 4,517,986 issued to Bilgutay teaches the use of a series of amplifiers with different sensitivities in order to correctly measure blood pressure from pressure pulse waves of different amplitudes. This patent, however, teaches only the use of a set of amplifiers with different transfer functions to amplify different parts of the pressure waveform. It does not teach selecting different points on the ROC curve, or using the divergence between simultaneous estimators as a measure of deriving information about blood pressure.
It is therefore a principal object of the present invention to provide a system and method for measuring physiological parameters that provide more information concerning the measured physiological parameter than known systems.
Another object of the present invention is to provide a system and method for measuring physiological parameters that uses multiple simultaneous estimators.
The system and method of the present invention provides information to the user of a medical monitoring or diagnostic device to aid in determining the true state of the measured parameter. The preferred embodiment uses two or more estimators or predictors of the same physiological process. Each of the estimators is designed to detect or predict either a specific state of the underlying parameter, or alternatively a type or class of artifact. Each estimator will therefore have a different sensitivity and specificity with respect to predicting a specific state or artifact, and thus will have a different operating point on the ROC curve corresponding to the prediction of that state or artifact. The estimators are designed such that they have similar values in the absence of the states or artifacts they are designed to predict. Furthermore, they are designed so that the degree of divergence between the estimators in the presence of specific states or artifacts will be similar across a population. The use of two or more estimators of the same parameter with different performance characteristics allows the user of the system and method of the present invention to derive information from not only the values of the estimators but also from the degree of their divergences. This enables the user to derive additional knowledge about the underlying measured parameter or state over and above that which would be available from a single estimator. The system and method of the present invention can derive information from not only the instantaneous values of the estimators and their divergences, but also from the time trend of the values of the estimators and their divergences.
These and other objects and features of the present invention will be more fully understood from the following detailed description which should be read in light of the accompanying drawings.